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The overall goal for this project was to reduce the incidence of COVID-19, hospitalization, and mortality among adults with serious mental illness (SMI) and intellectual disabilities/developmental disabilities (IDD) in congregate living settings (i.e., group homes) in Massachusetts, as well as to reduce COVID-19 incidence among staff who work in these settings. The research team was guided by two comparative effectiveness questions:

1. With the goal of prioritizing and making actionable best practices available as resources, what is the comparative effectiveness of various types and intensities of preventative interventions (e.g., screening, isolation, contact tracing, hand hygiene, physical distancing, use of face masks) in reducing rates of COVID-19, related hospitalizations, and related mortality in this population?
2. With the goal of effectively implementing best practices, what is the most effective implementation strategy to reduce rates of COVID-19 in this population: using tailored best practices (TBP) with SMI/IDD residents and staff of group homes in mind, or general best practices (GBP) from state and federal standard guidelines for all congregate care settings?

The specific aims of this study were as follows:

Aim 1a. Synthesize existing baseline data collected by 6 state behavioral health agencies on COVID-19 rates, hospitalization, mortality, and use of infection prevention practices.

Aim 1b. Collect stakeholder input via surveys and virtual focus groups on staff and resident experiences and on barriers/facilitators to implementing recommended preventative practices.

Aims 2a and 2b. Determine the comparative effectiveness of various COVID-19 preventative practices by (Aim 2a) using a validated simulation model to estimate COVID-19 spread in group homes and (Aim 2b) obtaining stakeholder input on prioritizing and defining tailored best practices for implementation.

Aim 3. Compare the effectiveness of TBPs with GBPs by using a hybrid effectiveness-implementation cluster randomized controlled trial.

Data collected to answer Aims 1 and 2 served as the foundation for designing the Aim 3 trial. Data for the trial were collected in 3-month intervals beginning January 2021 (baseline) until October 2022 (15-month follow-up). Residents and staff were sampled from approximately 400 group homes. Primary implementation outcome measures were COVID-19 vaccination rates and fidelity scores. The primary effectiveness outcome measure was COVID-19 infection.

Notes: This collection contains only data from Aim 1a and Aim 3. Throughout the data and documentation, "intellectual and/or developmental disabilities" is abbreviated as both IDD and ID/DD.

The COVID-19 Citizen Science (CCS) Study was launched early in the pandemic to collect patient-reported information about exposures, risk behaviors and outcomes relevant to the pandemic. The Patient-Centered Outcomes Research Institute (PCORI) funded the research team to expand recruitment into CCS using PCORnet, the National Patient-Centered Clinical Research Network, and to use the resulting data to compare the patient-reported impact of pandemic associated policies. The research team systematically collected pandemic-associated policies enacted by counties across the United States (focusing in areas where there were many CCS participants), and to do so on a weekly basis from the beginning of the pandemic using publicly available sources.

Researchers combined data from various sources to answer two primary research questions (RQ):

1. What is the comparative impact of different shelter-in-place/reopening policies, overall and in vulnerable populations, on patient-reported financial insecurity, mental health, and other subjective outcomes important to patients?
2. What is the comparative effectiveness of county-level containment and mitigation strategies at achieving timely access to COVID-19 vaccination, testing, healthcare, information and contact tracing?

The research team collected patient-reported data from the CCS study and policy data from the U.S COVID-19 County Policy (UCCP) database. Electronic health record (EHR) data were also available from some participants recruited from health systems located across 7 U.S. states who consented and authorized use of these data for the study. Data for these participants were extracted from the PCORnet Common Data Model (CDM). Additional county-level contextual variables were included in analysis.

This collection contains CCS survey data on patient-reported anxiety with county-level policies data (DS1), respondent demographics (DS2), baseline survey results (DS3), daily (DS4) and weekly (DS5) COVID-19 symptoms reports, COVID-19 vaccination surveys repeated monthly (DS6) as well as a one-time vaccination survey (DS7), and pandemic impacts check-in surveys (DS8). CDM datasets include logistic regression model outcomes to predict study enrollment among all invited participants (DS9), codes for immunizations (DS10), laboratory tests (DS11), and procedures (DS12). County-level variables are also available for years 2021 (DS13) and 2023 (DS14).

To study the impact of COVID-19 pandemic on frontline healthcare workers in the United States over time, the Healthcare Worker Exposure Response and Outcomes (HERO) Registry was created in 2020 to form a virtual research community of healthcare workers (and later, their family members and community members). The registry was intended for healthcare workers interested in completing research studies related to the COVID-19 pandemic and its impacts on their lives. Observational data were collected at various timepoints between April 2020 and September 2022 via web-based questionnaires available on the HERO Registry online portal.

This collection contains 39 sets of data from over 50,000 HERO Registry members. Datasets represent separate surveys with distinct survey designs and sampling criteria. Surveys focused on health history, workplace experiences, COVID-19 exposure, social support, mental health, and the respondents' willingness to remain in or leave the healthcare field. Datasets 24 through 39 represent "hot topics" such as vaccines, vaccine willingness and uptake, childcare and school arrangements, and staffing shortages. Datasets for registry administration, respondent demographics, and survey eligibility criteria are also included.